Jensen, Rachel

Abstract Background: Social determinants of health (SDOH) are critical drivers of cancer care access and outcomes. In multiple myeloma (MM), access to cellular therapies including autologous stem cell transplantation and CAR-T therapy often depends on formal or informal caregiver support. Traditional SDOH measures (e.g., race, income, or education) are often used as proxies for access to care; however, these measures may overlook individual realities pertaining to cellular therapies where a caregiver is generally required. In response to feedback from a HealthTree Patient Advisory Board questioning the practice of inferring caregiver support, this study evaluated a simple survey question by a large cross-sectional survey. Methods: After development of a dedicated single-question (“What best describes your current caregiving support?”) through iterative feedback from the Patient Advisory Board and MM experts, four key answers were settled on: (1) cohabitation with dedicated caregiver(s) to support care (“family support”); (2) presence of non-cohabiting caregiver(s) to provide dedicated support (“external support”); (3) lack of dedicated caregiver, hence support is arranged when needed (“arrangeable support ”); or (4) lack of dedicated caregiver, hence finding any support is a struggle (“inadequate support”). We deployed this new demographic question from February through July 2025 through HealthTree. Responses were analyzed across SDOH variables using Fisher exact or chi square tests, and random forest classifiers were employed for predictive modeling. Results: Of 1231 respondents, 71% had dedicated caregivers (68%, n=839, with family support, and 3%, n=41, with external support). In contrast, 23% (n=287) of patients routinely arranged support while 5% (n=64) had inadequate support (struggle to find support). The inadequate-support group had significant demographic differences from the sample as a whole: a higher proportion were women (78% vs 56%, p = 0.04), Black (9% vs 4%, p < 0.01), lived >50 miles from their treatment center (17% vs 6%, p < 0.01), and had an annual income <$50,000 (17% vs 6%, p = 0.02). This group had a numerically higher proportion of patients whose employment status was disabled (12% vs 5%, p=0.08) as well. No proportion difference in age (67 ± 9 yr), military status, or severity of diagnosis - precursor disease (17%) v. multiple myeloma (81%). Rates of inadequate support were overall low in patients who lived with only their spouse (1%) or lived with their spouse & children (3%). In contrast, rates of inadequate support were higher (than 5%) in patients who lived alone (21%), divorced (20%), lived with adult children (14%), lived with friends (13%), separated (11%), or widowed (9%) (p < 0.001). However, the arrangeable-support group comprised 12% of patients who lived only with their spouse, 19% of patients who lived with their spouse and children, and 61% of patients who lived with their adult children (p < 0.001). Finally, a random forest classifier failed to identify any individual in the inadequate-support category, suggesting that unmeasured or more complex patterns may underlie this classification. Conclusions: To our knowledge, this is the largest analysis of caregiver support and its relationship with other SDOH in patients with MM to date. Despite the importance of caregiving to transplantation and CAR-T therapy, we found that 5% of patients with MM struggle to find caregiver support; this figure likely underestimates the true prevalence, given potential selection bias among patients who are digitally engaged through the HealthTree platform. Even among patients who lived with their spouses, an additional 10-20% of patients routinely had to arrange caregiving support on a visit-by-visit basis; for patients who lived with their adult children, this proportion was over 60%. The requirement to arrange caregiving support can create time toxicity and financial toxicity for patients, although these factors were not directly queried in our study. Finally, caregiver availability cannot be routinely inferred from traditional SDOH variables. Our data highlight the importance of including caregiver status as a standard demographic question in clinical and research settings. Further interventions are needed to improve caregiver support for vulnerable patients with MM as well as to reduce the duration of caregiver requirements for procedures such as CAR-T therapy.

Introduction: Understanding patient preferences and decision-making processes is crucial in managing relapsed multiple myeloma (RRMM). Shared decision-making has become a key element of patient-centered care, allowing patients to collaborate with healthcare providers in choosing treatments that align with their health and quality of life goals. This study examines how the perceived severity of treatment side effects influences patient decision-making autonomy and communication patterns, providing insights into decision-making practices in hematology. Methods: A survey was conducted with 784 RRMM patients as of January 1, 2024, using HealthTree Cure Hub (PMID: 35271305). Among the participants, 333 experienced a relapse and responded to the question about how side effect severity affected their treatment choices. Of these, 54% (n=181) considered side effects to be very or extremely influential (VE), whereas 46% (n=152) regarded them as somewhat, slightly, or not influential at all (SSN). Participants evaluated these factors on 5-point Likert scales: 1 (very poor) to 5 (very good); 0 (not at all influential) to 4 (extremely influential). The survey assessed patient involvement in final treatment decisions, discussions with fellow patients, family or caregivers, and the time allocated and used for decision-making. Results: Patients in the VE group reported a better understanding of the likely side effects of treatment options compared to the SSN group (VE: 3.9±1.0; SSN: 3.6±1.0, p<0.05), with a higher proportion reporting a very good understanding (VE: 31%, n=45; SSN: 18%, n=29, p=0.036). A weak relationship confirmed VE patients engaged in additional side effect education before making a change in treatment decisions (r=0.164, p=0.004). VE patients also reported a better understanding of the balance between effectiveness and potential side effects of treatments than SSN patients (VE: 3.8±1.0; SSN: 3.5±1.1, p<0.05), with more VE patients reporting a very good understanding (29%, n=41 vs. 15%, n=24, p=0.006). A weak relationship confirmed that VE patients more closely evaluated the trade-offs of treatment options when choosing a new treatment regimen (r=0.197, p<0.001). Likely to achieve a better understanding, more VE patients talked with fellow patients (VE: 19%, n=24; SSN: 7%, n=11, p = 0.003) and rated these conversations as more influential than SSN (VE: 1.5±1.5; SSN: 1.1±1.4, p<0.05). Additionally, VE patients were more likely to discuss treatment options with family or caregivers before making a final decision (VE: 49%, n=61; SSN: 29%, n=43, p<0.05). Moreover, VE patients reported greater involvement in their doctor-patient communication approach (VE: 3.2±0.8; SSN: 2.8±0.8, p<0.05), with scores ranging from 1 (“...follow the doctor's suggestions”) to 4 (“...we discuss my preferences... and I make the final decision”). Furthermore, VE patients reported more self-determination in the treatment decision-making process than SSN patients, with more VE patients making the final treatment decision themselves rather than having their doctor decide (“I made the final decision” - VE: 66%, n=93; SSN: 52%, n=81; “My doctor made the final decision” - VE: 34%, n=47; SSN: 46%, n=72, p=0.013). VE patients reported being provided 1.5 more weeks of time to make a treatment decision than the SSN (4.8±8.9 v. 3.3±6.0 wks, p<0.05). Subsequently, VE patients reported using 79% more time than SSN patients to arrive at a final decision (VE: 2.5±6.0; SSN: 1.4±1.9 wks, p<0.05), likely attributed to time spent gaining a better understanding, having more conversations with patients and family, more shared decision making and self-determination in their treatment decision. Conclusion: The study highlights that RRMM patients who consider side effects to be very or extremely influential in their treatment decisions report being more proactive in understanding and discussing their treatment options. These patients engage more with healthcare providers, peers, and family members and are granted more time to make informed decisions. This emphasis on understanding and communication underscores the importance of personalized patient education and shared decision-making in the treatment of RRMM, especially for patients who are highly influenced by potential side effects. Together, these findings underscore the ongoing need for patient-centered care and education to optimize treatment choices.

Introduction: As therapeutic options for cancer increase at an unprecedented rate, understanding patient's awareness and attitudes is imperative to optimize their participation in shared decision making. Patient surveys are a powerful tool to gain insight into patient awareness but are cumbersome to administer on a large scale. With the advent of technology and virtual care, electronic surveys are being utilized more widely but their validity compared to approaching the patients in-person has not been established. We conducted a survey regarding awareness and preferences for clinical trials in-person and electronically and compared results systematically in a matched cohorts of patients with MM. Methods: A 52-question survey (including the domains: knowledge, trust, fear, external influence and optimism) was administered in-person to cancer patients at Mayo Clinic campuses (NCT04630431), of which patients with MM were identified for this analysis. The same survey was administered to MM patients enrolled in the online portal HealthTree® Cure Hub. Observations from the in-person and online cohorts were matched and weighted based on coarsened exact matching utilizing the “MatchIt” package based on age, gender, race, ethnicity, education, and marital status. Question responses were converted to an agreeance score scaled from 1 (Strongly Disagree) to 5 (Strongly Agree). Mean and standard deviation measurements were calculated. Weighted t-tests were conducted using these numeric scores and the matched weights. Results: Final matched cohorts included 83% (n=65) of the in-person and 69% (n=149) of the online participants. Mean age was 63.5 (± 8.5) years with 52% females for in-person vs. 65.9 (± 7.5) years and 54% females in the online participants. In-person cohort included 83% White, 14% Black and 12% Hispanic participants while online cohort had 94% White, 5% Black and 13% Hispanics/Latinos. Education level with 4-year degree or higher was reported by 66% in-person and 75% online participants. Both cohort respondents on average rated a strong likelihood of participating in a clinical trial (in-person 4.04, CI: 3.73-4.35; online 4.34, CI: 4.19-4.5). There was significant agreeance between the 2 cohorts on majority of the questionnaire domains. For basic knowledge about clinical trials, while none of the individual questions in the category were significantly different, the online group had a higher aggregate agreeance score of 3.91 vs. 3.73 for the in-person group with a significant difference of 0.18 (CI: 0.5-0.31, p=0.008). For external influence, the online group had a higher aggregate agreeance score (3.52) than the in-person group (3.15; Difference: 0.37, CI: 0.22-0.52, p<0.001), with the only question-level significant difference being for the question that regulatory agencies effectively control what is being advertised by the pharmaceutical industry (4.46 ± 0.64 vs. 3.48 ± 0.76, p<0.001). Conclusions: Online surveys are an effective tool for gaining insight into patient understanding, attitudes and awareness on a variety of topics and can be conducted efficiently on a larger scale than in-person studies, which may be more time and resource intensive. Our study provides evidence of general agreeance between a matched cohort of in-person and online survey respondents, providing validity to carefully conducted, planned online survey tools. The online cohort in our study overall had better knowledge about clinical trials and a better understanding about external influences on available clinical trial result information. These results will help boost studies to collect patient-level responses such that their beliefs and awareness can be better understood and incorporated in optimizing healthcare resource utilization.

Background A national survey of general surgery residents revealed significant self-assessed deficits in preparation for independent practice, with only 7.7% of graduating postgraduate year 5 residents (n=1145) reporting self-efficacy for all 10 commonly performed operations surveyed. Objective We sought to understand why this phenomenon occurs. We hypothesized that self-efficacy would be positively correlated with both operative independence and case volume. Methods We compared 3 independent datasets: case information for the same 10 previously surveyed operations for residents graduating in 2020 (dataset 1), operative independence data obtained through the SIMPL OR app, an operative self-assessment tool (dataset 2), and case volume data obtained through the Accreditation Council for Graduate Medical Education National Data Report (dataset 3). Operations were categorized into high, middle (mid), and low self-efficacy tiers; analysis of variance was used to compare operative independence and case volume per tier. Results There were significant differences in self-efficacy between high (87.7%), mid (68.3%), and low (25.4%) tiers ( P =.008 [95% CI 6.2, 32.7] for high vs mid, P <.001 for high vs low [49.1, 75.6], and P <.001 for mid vs low [28.7, 57.1]). The percentage of cases completed with operative independence followed similar trends (high 32.7%, mid 13.8%, low 4.9%, P =.006 [6.4, 31.4] for high vs mid, P <.001 [15.3, 40.3] for high vs low, P =.23 [-4.5, 22.3] for mid vs low). The total volume of cases decreased from high to mid to low self-efficacy tiers (average 91.8 to 20.8 to 11.1) but did not reach statistical significance on post-hoc analysis. Conclusions In this analysis of US surgical residents, operative independence was strongly correlated with self-efficacy.